1. Field of the Invention
The present invention relates to a system for providing home healthcare management. More specifically, the present invention relates to a home healthcare system for providing home diagnoses, testing, and management of the information derived therefrom.
2. Description of the Related Art
Medical Diagnosis & Diagnostics
Throughout recorded time health care has increasingly relied upon trained healthcare personnel. This was in part due to the limited availability of education, and due to the limited access to medical knowledge bases. Prior to the general availability of the Internet, patients had to rely on limited medical resources.
Medical training includes four years of learning medical terminology and pathophysiological relationships, and many additional post-graduate training years to develop and understand the patient's contextual constructs for describing their disease, i.e., weighting factors and parsing important and tangential symptoms. Many have attempted to translate the complex pathophysiological relationships and interrelationships that they learned in medical school and through experience, into algorithms, branching trees, likelihood ratios, probabilities, tables and the like; sometimes referring to them as traditional medicine or evidence-based medicine. This is akin to behavior modeling of relationships which while adequate for predicting group behavior, falls short of predicting individual behaviors, needs and responses.
The translation of medical knowledge into a series of questions that can lead the patient into a diagnosis is cumbersome, impractical and fraught with error. By example, telephone answering services are a simplified implementation of this method. Press 1 for the following services, press 2 for the following services, etc., ostensibly guiding the listener to a final service. Often the listener is uncertain that the press 1 service is exactly what they are looking for, and may try another, ending up at an incorrect end-point. While on paper the flow and logic directing a listener to a particular service may seem clear, the listener does not have the advantage of context and will thus have a different interpretation of various words and may come to a different conclusion. Analogously, while a disease may have a common cause, the effects on the patient and how it is perceived is unique for every patient. Consequently, the current practice is to use health care professionals to map a patient's symptoms to current medical terminology and understanding and then recommend tests to drill down to the underlying cause, (e.g., iterative testings).
It is common for an illness as simple as a sore throat to take hours or days to evaluate. Time is spent 1) making an appointment; 2) adjusting the work schedule to accommodate the appointment; 3) driving to the appointment; 4) waiting to be seen; 5) testing; 6) waiting for the results from a distant laboratory; and 7) traveling back to work. And if test results are inconclusive, more tests are needed the next day. In other words the current health care model is comprised of: a health care provider who evaluates symptoms and selects the appropriate tests, support personnel that conduct the tests relaying the results back to the provider, and the provider determining if more tests are necessary. With rising health care costs, testing has become judicious as a cost cutting measure. Testing can be expensive because it includes the cost of the facilities to house the test and personnel, the cost of the instrument that conducts the tests, the government certification and compliant costs, the personnel costs to draw blood, personnel to maintain instruments, personnel to certify compliance, the cost of the test itself, and the administrative costs (e.g., computers, personnel, accounting, health care insurance, etc). As a result of Enterprise pressures to cut costs, patients are inadequately tested, and the patient's symptoms often are allowed to progress into more easily identified symptoms, i.e., they are diagnosed at a later time using less expensive means.
Enterprise systems (e.g., health maintenance organizations (HMOs), participating provider option (PPOs), Medicare and Medicaid, Public Health Care services, physician groups, etc.) are physician and business centric; most decisions stem from these two primaries. Physicians make diagnoses, recommend testing, and choose what will be entered into the patients history; business administrators review patients records, recommend tests, review photographs, and decide how widely the patients records will be disseminated and what tests will be reimbursed. Patients have little or no control over the sharing and review of confidential information, who views the before and after photographs nor the extent to which they are reimbursed. In addition to the issue of non-medical personnel reviewing records and photos, there is an issue of security where servers are broken into or files, taken home on laptops, are by third parties.
The point-of-care (POC) market generally refers to urgent care clinics, emergency room services, physician offices, and assisted care facilities, which are all staffed by trained health care professionals. These are federally regulated laboratories under the Food and Drug Administration (FDA) and Clinical Laboratory Improvement Amendments (CLIA); Federal law requires trained professionals to maintain and operate the equipment within compliance standards. CLIA regulated laboratories must maintain and disseminate data and test results within CLIA guidelines.
Over-the-counter tests are available for home care testing, e.g., drug screening, antigen testing, glucose testing, and urine testing. However, the number of tests is limited due to the special instrumentation and computer processing required. Glucose testing is one of the outlying cases where specialized instrumentation has developed to support testing at home; but, a system for selecting and running additional related diagnostic tests and comprehensive at home health care support system does not exist. More importantly, the physician typically makes the diagnosis, such as a diagnosis of diabetes, and directs the patient to self-test for glucose and also provides treatment guidance.
Health care costs continue to soar in spite of newer technologies purporting to reduce cost; primary care providers cannot support the 300 million people in the United States, and the spill-over is disrupting emergency care facilities. The medical paradigm of physician centric primary care is unable to sustain the quality of patient care administered two decades ago.
Digital Microscopy
Microscopy can be divided into three hardware categories: 1) Optical microscopy, wherein an enlarged sample image is displayed through an ocular assembly onto the observer's retina; 2) Digital microscopy, wherein a sample image is displayed onto a camera or other photosensitive device; and, 3) Hybrid microscopy, wherein an enlarged sample image can be displayed onto a retina or camera.
Digital microscopes are used to enlarge an object, for example a red blood cell in a whole blood smear, but are not designed for colorimetric or fluorometric laboratory assays such as glucose testing, antigen testing and the like. The design and operation of a digital microscope in a small form factor has extremely dense complexities; vibration from PC fans are transferred to the microscope slide, xyz translations and illumination must be conducted within the voltage and power constraints of the PC power supply, illumination and imaging paths must be substantially shorter, and image quality should be comparable to a standard optical microscope.
To reduce vibration, microscopes are set on a low vibration table. If an image is to be captured by a camera, the sample is translated into position and then time is allocated for the sample stage to settle down from the translation before the image is finally captured. A component of the translation vibration comes from stacking x and y translation tables upon one another. Each level, from the base to the top translation level, vibrates the level above it, and that vibration is magnified so that the top level vibrates the most.
Microscopes utilize an objective to collect, magnify, and infinity correct an image. The infinity correction serves to establish a light path in which other optical elements can be inserted with minor impact on the image. The tradeoff is a considerably larger objective size, more optical elements in the objective, greater difficulty in assembling and aligning the optical elements, and the need to extend the optical path beyond the objective, i.e., where an additional set of optical elements are required for image formation. Over the last 100 years microscope manufactures have moved toward lengthening the optical path, therein increasing the overall size of the microscope. An infinity corrected objective often requires a greater than 160 mm optical path.
In digital microscopy, many images are captured from scanning a microscope slide, which is assembled and displayed on an LCD display. The stage holding the slide is precisely positioned to enable image capture yet maintain image registration, i.e., of the tens of thousands of rows and columns all must be kept in perfect alignment. Current methods rely on the precision encoders and closed loop systems to determine movement distance, and they have based their methods upon the very high resolution of those encoders; they require better than 100 nm resolutions. They have developed slide coordinate systems that map encoder coordinates to locations on the slide, and they use those slide mapped coordinates for tiling and to avoid image overlap. The intent is that when an image is viewed on a display every displayed pixel has a corresponding coordinate on the scanned slide. However, when a slide is removed from a digital microscope and later placed back into the same position in the same digital microscope, the original encoder coordinates are no longer valid.
Relying on the fixed coordinate approach to scan and tile slides is costly, cumbersome, and fraught with error. Encoders are expensive and add complexity and points of failure. Moreover, others have confused encoder resolution with accuracy. It is not generally known that, although encoders have very high resolution (in many cases better that 20 nm), the absolute positional accuracy is only approximately 3,000 nm. Moreover, the absolute accuracy is only valid in a specific environment at a precise temperature. In a microscope stage environment, invariably the thermal gradients and transitions deform the metals holding the slide and encoder by 100,000 nm or more. Metal deformations degrade an absolute coordinate system.
Relying on encoders for abutting image tiles can lead to erroneous image results due to the absolute positional inaccuracy. For example, if a specific lot of encoders is used for deriving a coordinate system, and that lot is 3,000 nm longer than it should be, images collected and assembled based on that coordinate system will be distorted; this could possibly misdirect a clinical decision. This is especially true of line scan cameras.
With the transition to digital media and Internet transfer of medical records, there is a greater need for medical record security and tamper prevention. To detect tampering, digital images can be scanned for distortions using various algorithms known in the art. Certain acquisition distortions from encoder positional inaccuracies could be falsely construed as tampering.
Encoders that resolve better than 100 nm are primarily based on laser interferometry techniques. Encoders, in general, add cost to the system, increase the degree of electrical and software complexity increase assembly and maintenance costs, and add another possible failure point.
To assemble a macro composite of the entire tissue sample on a microscope slide, the tissue is first magnified thereby limiting the field of view to only a portion of the tissue sample. Those magnified images are tiled to form a larger magnified image of the entire tissue sample—a so called panoramic or composite image. At high magnifications, tens of thousands of tiles may need to be collected to form a composite macro image. Consequently, a physician that is only interested in the general appearance of one small section of tissue has to wait until the entire tissue is scanned and processed. Not only is this costly in time, but a typical pathology laboratory would generate terabytes of useless data that federal law mandates must be properly stored for many years, backed up, and security maintained.
Displays have a limited size and only a limited amount of information can be displayed. Superfluous images of virtual microscope slides, as is seen in the prior art, unnecessarily displaces important information. Displaying only the tissue sample, i.e., the object on the microscope slide, leaves room for other information.
There is significant programming and file overhead with the prior art coordinate based image tiling. A header file is needed for coordinate translation, and if lost or corrupted, image formation can fail. Additionally, image display is slow—when a file is downloaded from the hard drive it must first go through a coordinate translation algorithm that is unique to coordinate based image tiling to derive the image display coordinates.
Others have suggested methods for positioning by using overlapping images and correcting positioning errors by determining positioning error within the overlapping regions of consecutive images. Thus, two images must be captured that overlap. A mismatch in image registration is determined and translated into a coordinate offset error that is added to the position coordinates for the third captured image: wherein all three images are displayed. Consequently, rounding errors and offset error inaccuracies accumulate with every captured image. The accumulated error distorts both column and row alignment of tiled images. To overcome the distortion, each image must have a large number of overlapping pixels around the entire image periphery. Since each image includes positional error, capturing 50 images in one direction would require at least 50 times the positional error in overlapping pixels to compensate for accumulated distortion. This method requires a more expensive camera because of the extra pixels required to overlap images. Segmentation algorithms for calculating mal-alignment are inaccurate, slow, and computationally intensive. And, preprocessing images to strip out unused pixels in overlapping area around the image periphery requires significant computation time thereby further slowing down storage.
Processing
Electronic detection methods have advanced to the point where they are far more sensitive and less variable than the constituents in a biological assay. Biological assays have matured to a point where chemical species, proteins, and genetic components can be detected at the molecular level. However, such detection methods require a specific sequence of preparation that is beyond the training of the average person. In a hospital setting, where hundreds of samples have to be prepared each day, preparation and analysis is fully automated. Automation comes at a substantial price: capital equipment costs, federal regulatory certification costs, training costs, maintenance costs, and facilities costs. And, the automation equipment is not disposable. Consequently, many diagnostic tests cannot be run in small laboratories, physician offices, or at patient homes. This is especially true of PCR assays, where processing errors are poorly tolerated and the processing methods and temperatures are more complex.
Methods of moving fluids through pipes and channels have been around for centuries. In the last half of the last century, High Pressure Liquid Chromatography (HPLC) pioneered the miniaturization of fluid channels through the use of capillary tubing and rotary valves. Rotary valves generally consist of a set of disks of varying aspect ratios as layers and in contact with one another, which have channels in the intervening layers to divert fluid from an opening in the top layer to a predetermined opening in the bottom layer. Fluid will flow under pressure from the input through lateral channels to output. As the channels became smaller and smaller there was an exponential increase in force required to overcome surface tension, wall adherence, and maintain laminar flow. Air pressure, vacuum, column pressure, pumps, electromotive force, and centrifugation are required to move small volumes, especially for lateral movement—the fluid surface area for adherence to the wall exponentially increases as the volume decreases. Certain materials related to Delran and high molecular weight polypropylenes may reduce adherence but none eliminate adherence. Therefore, at small volumes, if a significant portion of the fluid surface is in contact with a channel wall (in proportion to the volume) pressure, something other than gravitational feed is required.
Many processes require a washing step to remove interfering constituents. Washing often uses centrifugation to pellet beads or cells or other constituents, and decanting the waste fluid. This is an extra procedural step that involves other equipment. A washing step limits the use of many assays to skilled personnel.
Many assays require thermal management—especially PCR assays where thermal management is complex. Thermal cyclers raise and lower temperature in discrete preprogrammed steps or establish annealing temperatures for primers. They can be heavy and costly, and they are not disposable. Reaction tubes containing the analyte must be in close contact with the thermal cycler for proper temperature control. The thermal contact issue is often problematic and can be overcome with PCR oil. This is one of the technical difficulties that has impeded the general introduction of genetic testing.
Size, durability, and reliability are focus issues for first responder emergencies e.g., anthrax release, bioterrorism, avian flu pandemic, where assays need to be run immediately without prior training, or in difficult terrain such as in a cave, or in a situation where diverting attention to the assay could prove deadly. Assays that are as small as a stack of coins can be stockpiled and moved in large quantities quickly. Small, fully automated assays which can be run by anyone without training both improve reliability and enables general availability of that assay.